Text Dependent Speaker Recognition using MFCC features and BPANN
N Praveen, Tessamma Thomas · International Journal of Computer Applications · 2013
Mel-Frequency Cepstral Coefficients are spectral feature which are widely used for speaker recognition and text dependent speaker recognition systems are the most accurate in voice based authentication systems.In this paper, a text dependent speaker recognition method is developed.MFCCs are computed for a selected sentence.The first 13 MFCCs are considered for each frames of duration 26ms and each coefficient is clustered to a 5 element cluster centres and finally to a form a 65 element speech code vector for the entire speech.The speech code is trained using a multi-layer perceptron backpropagation gradient descent network and the network is tested for various test patterns.The performance is measured using FAR, FRR and EER parameters.The recognition rate achieved is 96.18% for a cluster size of 5 in each coefficient.